The goal of this proposal is to determine if one can improve models of age-related decline on a "real world" ',ognitive task by adding assessments of longitudinal brain volume changes to the model. We will collect longitudinal structural MRI data on a subset of the 100+ aviators participating in our ongoing longitudinal study of pilot performance: 60 subjects, 55 years of age or older, will be scanned three times each across a span of four years (Y0, Y2, Y4). Half of the sample will possess an Apolipoprotein E (APOE) epsilon 4 allele (e4 carriers), a genetic risk factor for Alzheimer's disease. Our primary hypotheses are: Annualized rate of atrophy, as assessed by longitudinal MR volumetric measures, can account for individual differences in the rate of decline in flight simulator performance, beyond that explained by measures of processing speed and working memory, APOE e4 carrier status, and aviation experience. We will also examine whether baseline MR measures are as useful as longitudinal MR measures, for the aim of ach ev ng earl er identification of individuals at risk of decline. Volumetric measures of hippocampus and frontal lobe will be the MR predictors in the primary hypothesis, as our perspective is that safely flying an airplane to its intended destination involves memory for routes and multi-tasking skills. The primary outcome measure is rate of decline in flight summary scores, using a highly quantified flight simulator test involving multi-tasking. For several years we have been following a group of older small-aircraft pilots' performance in a quantified flight simulator. Data clearly show effects of age on performance; however, there is substantial heterogeneity in performance over time among aviators. We propose to enhance our set of predictors by the addition of highly quantified MR volumetric measures to better explain in whom and how functional decline OCCU rs.